Pipeline to Detect Chemicals and Proteins in text

Description

This pretrained pipeline is built on the top of ner_chemprot_biobert model.

Predicted Entities

GENE-N, CHEMICAL, GENE-Y

Copy S3 URI

How to use

pipeline = PretrainedPipeline("ner_chemprot_biobert_pipeline", "en", "clinical/models")


pipeline.annotate("Keratinocyte growth factor and acidic fibroblast growth factor are mitogens for primary cultures of mammary epithelium.")
val pipeline = new PretrainedPipeline("ner_chemprot_biobert_pipeline", "en", "clinical/models")


pipeline.annotate("Keratinocyte growth factor and acidic fibroblast growth factor are mitogens for primary cultures of mammary epithelium.")
import nlu
nlu.load("en.med_ner.chemprot_biobert.pipeline").predict("""Keratinocyte growth factor and acidic fibroblast growth factor are mitogens for primary cultures of mammary epithelium.""")

Results

+-------------------------------+--------+
|chunks                         |entities|
+-------------------------------+--------+
|Keratinocyte growth factor     |GENE-Y  |
|acidic fibroblast growth factor|GENE-Y  |
+-------------------------------+--------+

Model Information

Model Name: ner_chemprot_biobert_pipeline
Type: pipeline
Compatibility: Healthcare NLP 3.4.1+
License: Licensed
Edition: Official
Language: en
Size: 422.0 MB

Included Models

  • DocumentAssembler
  • SentenceDetectorDLModel
  • TokenizerModel
  • BertEmbeddings
  • MedicalNerModel
  • NerConverter